In wireless sensor networks a large amount of data is collected for each node. The challenge of trans-ferring these data to a sink, because of energy constraints, requires suitable techniques such as datacompression. Transform-based compression, e.g. Discrete Wavelet Transform (DWT), are very popularin this field. These methods behave well enough if there is a correlation in data. However, especiallyfor environmental measurements, data may not be correlated. In this work, we propose two approachesbased on F-transform, a recent fuzzy approximation technique. We evaluate our approaches with Dis-crete Wavelet Transform on publicly available real-world data sets. The comparative study shows thecapabilities of our approaches, which allow a higher data compression rate with a lower distortion, evenif data are not correlated.

Multisignal 1D-compression by F-transform for wireless sensor networks applications

GAETA, Matteo;LOIA, Vincenzo;TOMASIELLO, Stefania
2015

Abstract

In wireless sensor networks a large amount of data is collected for each node. The challenge of trans-ferring these data to a sink, because of energy constraints, requires suitable techniques such as datacompression. Transform-based compression, e.g. Discrete Wavelet Transform (DWT), are very popularin this field. These methods behave well enough if there is a correlation in data. However, especiallyfor environmental measurements, data may not be correlated. In this work, we propose two approachesbased on F-transform, a recent fuzzy approximation technique. We evaluate our approaches with Dis-crete Wavelet Transform on publicly available real-world data sets. The comparative study shows thecapabilities of our approaches, which allow a higher data compression rate with a lower distortion, evenif data are not correlated.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4620857
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